Papers
11
Total Citations
102
H-Index
7
About
Luca Tagliapietra is a researcher at the intersection of robotics, biomechanics, and neuroscience, with key contributions in human motion estimation, brain-machine interfaces (BMI), and deep reinforcement learning for robotic manipulation. His most cited work (2018, 29 citations) validates a model-based inverse kinematics approach using wearable inertial sensors (IMUs) to accurately estimate joint angles, a breakthrough for human motion analysis and rehabilitation. He also developed ROS-Neuro (2019, 15 citations), a middleware bridging BMI and robotics for brain-actuated neuroprostheses, and introduced a deep reinforcement learning framework for tabletop object sorting (2019, 11 citations). Tagliapietra’s open-source contributions include Hi-ROS (2023, 10 citations), a multi-camera sensor fusion system for real-time people tracking, and a ROS driver for Xsens IMU systems (2021, 7 citations), enabling scalable motion capture. His work on estimating EMG signals for neuromusculoskeletal models (2015, 8 citations) advances neurorehabilitation by decoding patient intent. With over 90 total citations across these papers, Tagliapietra’s research is pivotal for developing intuitive, human-aware robotic systems, from assistive devices to rehabilitation technologies.
Research Focus
Key Achievements
Top Papers
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- 4Hi-ROS: Open-source multi-camera sensor fusion for real-time people tracking10 citations · 2023
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- 7A ROS Driver for Xsens Wireless Inertial Measurement Unit Systems7 citations · 2021
- 8Design of a Subject-Specific EMG Model for Rehabilitation Movement4 citations · 2014
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- 10Neural and Musculoskeletal Modeling: Its Role in Neurorehabilitation3 citations · 2015